Deep Learning for Roman Handwritten Character Recognition
- 1. Universiti Teknologi MARA
Description
The advantage of deep learning is that the analysis and learning of massive amounts of unsupervised data make it a beneficial tool for Big Data analysis. Convolution Neural Network (CNN) is a deep learning method that can be used to classify image, cluster them by similarity, and perform image recognition in the scene. This paper conducts a comparative study between three deep learning models, which are simple-CNN, AlexNet and GoogLeNet for Roman handwritten character recognition using Chars74K dataset. The produced results indicate that GooleNet achieves the best accuracy but it requires a longer time to achieve such result while AlexNet produces less accurate result but at a faster rate.
Files
03 14425 Deep Learning for edit iqbal.pdf
Files
(736.6 kB)
Name | Size | Download all |
---|---|---|
md5:366cc683900dff260fbdf4d767acba4c
|
736.6 kB | Preview Download |